Change type of attribute bpolys to Feature

workers/ohsome_quality_analyst/api.py

@@ -63,29 +63,32 @@ def int_or_str_param_type(value: str) -> Union[int, str]:
             raise ValueError("Given parameter is not a valid integer or string")
 
 
-async def load_bpolys(bpolys: str) -> Union[Polygon, MultiPolygon]:
+async def load_bpolys(bpolys: str) -> Feature:
     """Load as GeoJSON object, validate and check size of bpolys"""
     # TODO: Return API response with error message
+
+    async def check_geom_size(geom):
+        if await db_client.get_area_of_bpolys(geom) > GEOM_SIZE_LIMIT:
+            raise ValueError(
+                "Input GeoJSON Object is too big. "
+                + "The area should be less than {0} sqkm.".format(GEOM_SIZE_LIMIT)
+            )
+
     bpolys = geojson.loads(bpolys)
 
     if bpolys.is_valid is False:
         raise ValueError("Input geometry is not valid")
-
-    if isinstance(bpolys, Feature):
-        bpolys = bpolys["geometry"]
-
-    if isinstance(bpolys, (Polygon, MultiPolygon)) is False:
+    elif isinstance(bpolys, Feature):
+        await check_geom_size(bpolys.geometry)
+        return bpolys
+    elif isinstance(bpolys, (Polygon, MultiPolygon)):
+        await check_geom_size(bpolys)
+        return Feature(geometry=bpolys)
+    else:
         raise ValueError(
             "Input GeoJSON Objects have to be of type Feature, Polygon or MultiPolygon"
         )
 
-    if await db_client.get_area_of_bpolys(bpolys) > GEOM_SIZE_LIMIT:
-        raise ValueError(
-            "Input GeoJSON Object is too big. "
-            + "The area should be less than {0} sqkm.".format(GEOM_SIZE_LIMIT)
-        )
-    return bpolys
-
 
 @app.get("/indicator/{name}")
 async def get_indicator(
@@ -184,7 +187,11 @@ async def _fetch_report(
         feature_id = int_or_str_param_type(feature_id)
 
     report = await oqt.create_report(
-        name, bpolys=bpolys, dataset=dataset, feature_id=feature_id, fid_field=fid_field
+        name,
+        feature=bpolys,
+        dataset=dataset,
+        feature_id=feature_id,
+        fid_field=fid_field,
     )
 
     response = empty_api_response()

workers/ohsome_quality_analyst/base/indicator.py

@@ -7,11 +7,11 @@
 from dataclasses import dataclass
 from datetime import datetime
 from io import StringIO
-from typing import Dict, Literal, Optional, Union
+from typing import Dict, Literal, Optional
 
 import matplotlib.pyplot as plt
 from dacite import from_dict
-from geojson import MultiPolygon, Polygon
+from geojson import Feature
 
 from ohsome_quality_analyst.utils.definitions import (
     INDICATOR_LAYER,
@@ -63,11 +63,10 @@ class BaseIndicator(metaclass=ABCMeta):
     def __init__(
         self,
         layer_name: str,
-        bpolys: Union[Polygon, MultiPolygon],
+        feature: Feature,
         data: Optional[dict] = None,
     ) -> None:
-
-        self.bpolys = bpolys
+        self.feature = feature
         self.data = data
 
         # setattr(object, key, value) could be used instead of relying on from_dict.

workers/ohsome_quality_analyst/base/report.py

@@ -2,10 +2,10 @@
 from abc import ABCMeta, abstractmethod
 from dataclasses import dataclass
 from statistics import mean
-from typing import Dict, List, Literal, NamedTuple, Optional, Tuple, Union
+from typing import Dict, List, Literal, NamedTuple, Optional, Tuple
 
 from dacite import from_dict
-from geojson import MultiPolygon, Polygon
+from geojson import Feature
 
 from ohsome_quality_analyst.base.indicator import BaseIndicator
 from ohsome_quality_analyst.utils.definitions import get_metadata
@@ -39,15 +39,15 @@ class BaseReport(metaclass=ABCMeta):
 
     def __init__(
         self,
-        bpolys: Union[Polygon, MultiPolygon, None] = None,
+        feature: Feature = None,
         dataset: Optional[str] = None,
         feature_id: Optional[int] = None,
         fid_field: Optional[str] = None,
     ):
         self.dataset = dataset
         self.feature_id = feature_id
         self.fid_field = fid_field
-        self.bpolys = bpolys
+        self.feature = feature
 
         # Definies indicator+layer combinations
         self.indicator_layer: Tuple[IndicatorLayer] = []

workers/ohsome_quality_analyst/cli.py

@@ -124,7 +124,7 @@ def create_indicator(
                 oqt.create_indicator(
                     indicator_name,
                     layer_name,
-                    bpolys=feature.geometry,
+                    feature=feature,
                     feature_id=feature_id,
                     dataset=dataset_name,
                     fid_field=fid_field,
@@ -143,7 +143,7 @@ def create_indicator(
             oqt.create_indicator(
                 indicator_name,
                 layer_name,
-                bpolys=None,
+                feature=None,
                 feature_id=feature_id,
                 dataset=dataset_name,
                 fid_field=fid_field,
@@ -153,12 +153,9 @@ def create_indicator(
         if outfile:
             if fid_field is None:
                 fid_field = DATASETS[dataset_name]["default"]
-            feature_collection = asyncio.run(
-                db_client.get_bpolys_from_db(dataset_name, feature_id, fid_field)
-            )
-            for feature in feature_collection.features:
-                feature = update_features_indicator(feature, indicator)
-            write_geojson(outfile, feature_collection)
+            feature = asyncio.run(db_client.get_region_from_db(feature_id, fid_field))
+            feature = update_features_indicator(feature, indicator)
+            write_geojson(outfile, feature)
         else:
             click.echo(indicator.metadata)
             click.echo(indicator.result)
@@ -190,7 +187,7 @@ def create_report(
             report = asyncio.run(
                 oqt.create_report(
                     report_name,
-                    bpolys=feature.geometry,
+                    feature=feature,
                     dataset=dataset_name,
                     feature_id=feature_id,
                     fid_field=fid_field,
@@ -208,7 +205,7 @@ def create_report(
         report = asyncio.run(
             oqt.create_report(
                 report_name,
-                bpolys=None,
+                feature=None,
                 dataset=dataset_name,
                 feature_id=feature_id,
                 fid_field=fid_field,
@@ -218,12 +215,9 @@ def create_report(
         if outfile:
             if fid_field is None:
                 fid_field = DATASETS[dataset_name]["default"]
-            feature_collection = asyncio.run(
-                db_client.get_bpolys_from_db(dataset_name, feature_id, fid_field)
-            )
-            for feature in feature_collection.features:
-                feature = update_features_report(feature, report)
-            write_geojson(outfile, feature_collection)
+            feature = asyncio.run(db_client.get_region_from_db(feature_id, fid_field))
+            feature = update_features_report(feature, report)
+            write_geojson(outfile, feature)
         else:
             click.echo(report.metadata)
             click.echo(report.result)

workers/ohsome_quality_analyst/geodatabase/client.py

@@ -21,7 +21,7 @@
 
 import asyncpg
 import geojson
-from geojson import FeatureCollection, MultiPolygon, Polygon
+from geojson import Feature, FeatureCollection, MultiPolygon, Polygon
 
 from ohsome_quality_analyst.utils.definitions import DATASETS
 
@@ -148,22 +148,21 @@ async def get_area_of_bpolys(bpolys: Union[Polygon, MultiPolygon]):
     return result["area_sqkm"]
 
 
-# TODO: Return GeoJSON object of type Polygon or MultiPolygon not FeatureCollection
-async def get_bpolys_from_db(
-    dataset: str, feature_id: Union[int, str], fid_field: str
-) -> Union[Polygon, MultiPolygon]:
-    """Get bounding polygon from the geodatabase as a GeoJSON FeatureCollection."""
-    logging.info("(dataset, fid_field, id): " + str((dataset, fid_field, feature_id)))
+async def get_region_from_db(feature_id: Union[int, str], fid_field: str) -> Feature:
+    """Get regions from geodatabase as a GeoJSON Feature object"""
+    logging.info("(fid_field, id): " + str((fid_field, feature_id)))
 
     # Safe against SQL injection because of predefined values
     # (See oqt.py and definitions.py)
-    query = "SELECT ST_AsGeoJSON(geom) FROM {dataset} WHERE {fid_field} = $1".format(
-        fid_field=fid_field, dataset=dataset
+    query = (
+        "SELECT ST_AsGeoJSON(geom) "
+        + "FROM regions "
+        + "WHERE {0} = $1".format(fid_field)
     )
 
     async with get_connection() as conn:
         result = await conn.fetchrow(query, feature_id)
-    return geojson.loads(result[0])
+    return Feature(geometry=geojson.loads(result[0]))
 
 
 async def get_available_regions() -> FeatureCollection:

workers/ohsome_quality_analyst/indicators/ghs_pop_comparison_buildings/indicator.py

@@ -1,12 +1,11 @@
 import logging
 from io import StringIO
 from string import Template
-from typing import Union
 
 import matplotlib.pyplot as plt
 import numpy as np
 from asyncpg import Record
-from geojson import MultiPolygon, Polygon
+from geojson import Feature
 
 from ohsome_quality_analyst.base.indicator import BaseIndicator
 from ohsome_quality_analyst.geodatabase import client as db_client
@@ -19,11 +18,11 @@ class GhsPopComparisonBuildings(BaseIndicator):
     def __init__(
         self,
         layer_name: str,
-        bpolys: Union[Polygon, MultiPolygon],
+        feature: Feature,
     ) -> None:
         super().__init__(
             layer_name=layer_name,
-            bpolys=bpolys,
+            feature=feature,
         )
         # Those attributes will be set during lifecycle of the object.
         self.pop_count = None
@@ -45,14 +44,16 @@ def yellow_threshold_function(self, pop_per_sqkm) -> float:
         return 0.75 * np.sqrt(pop_per_sqkm)
 
     async def preprocess(self) -> bool:
-        pop_count, area = await self.get_zonal_stats_population(bpolys=self.bpolys)
+        pop_count, area = await self.get_zonal_stats_population()
 
         if pop_count is None:
             pop_count = 0
         self.area = area
         self.pop_count = pop_count
 
-        query_results = await ohsome_client.query(layer=self.layer, bpolys=self.bpolys)
+        query_results = await ohsome_client.query(
+            layer=self.layer, bpolys=self.feature.geometry
+        )
         if query_results is None:
             return False
         self.feature_count = query_results["result"][0]["value"]
@@ -172,7 +173,7 @@ def create_figure(self) -> bool:
         plt.close("all")
         return True
 
-    async def get_zonal_stats_population(self, bpolys: dict) -> Record:
+    async def get_zonal_stats_population(self) -> Record:
         """Derive zonal population stats for given GeoJSON geometry.
 
         This is based on the Global Human Settlement Layer Population.
@@ -198,6 +199,6 @@ async def get_zonal_stats_population(self, bpolys: dict) -> Record:
                 st_setsrid(public.ST_GeomFromGeoJSON($3), 4326)
              )
             """
-        data = tuple(map(str, [bpolys] * 3))
+        data = tuple(map(str, [self.feature.geometry] * 3))
         async with db_client.get_connection() as conn:
             return await conn.fetchrow(query, *data)

workers/ohsome_quality_analyst/indicators/ghs_pop_comparison_roads/indicator.py

@@ -1,12 +1,11 @@
 import logging
 from io import StringIO
 from string import Template
-from typing import Union
 
 import matplotlib.pyplot as plt
 import numpy as np
 from asyncpg import Record
-from geojson import MultiPolygon, Polygon
+from geojson import Feature
 
 from ohsome_quality_analyst.base.indicator import BaseIndicator
 from ohsome_quality_analyst.geodatabase import client as db_client
@@ -19,12 +18,9 @@ class GhsPopComparisonRoads(BaseIndicator):
     def __init__(
         self,
         layer_name: str,
-        bpolys: Union[Polygon, MultiPolygon],
+        feature: Feature,
     ) -> None:
-        super().__init__(
-            layer_name=layer_name,
-            bpolys=bpolys,
-        )
+        super().__init__(layer_name=layer_name, feature=feature)
         # Those attributes will be set during lifecycle of the object.
         self.pop_count = None
         self.area = None
@@ -47,14 +43,16 @@ def yellow_threshold_function(self, pop_per_sqkm) -> float:
             return 5
 
     async def preprocess(self) -> bool:
-        pop_count, area = await self.get_zonal_stats_population(bpolys=self.bpolys)
+        pop_count, area = await self.get_zonal_stats_population()
 
         if pop_count is None:
             pop_count = 0
         self.area = area
         self.pop_count = pop_count
 
-        query_results = await ohsome_client.query(layer=self.layer, bpolys=self.bpolys)
+        query_results = await ohsome_client.query(
+            layer=self.layer, bpolys=self.feature.geometry
+        )
         if query_results is None:
             return False
         # results in meter, we need km
@@ -169,7 +167,7 @@ def create_figure(self) -> bool:
         plt.close("all")
         return True
 
-    async def get_zonal_stats_population(self, bpolys: dict) -> Record:
+    async def get_zonal_stats_population(self) -> Record:
         """Derive zonal population stats for given GeoJSON geometry.
 
         This is based on the Global Human Settlement Layer Population.
@@ -195,6 +193,6 @@ async def get_zonal_stats_population(self, bpolys: dict) -> Record:
                 st_setsrid(public.ST_GeomFromGeoJSON($3), 4326)
              )
             """
-        data = tuple(map(str, [bpolys] * 3))
+        data = tuple(map(str, [self.feature.geometry] * 3))
         async with db_client.get_connection() as conn:
             return await conn.fetchrow(query, *data)

workers/ohsome_quality_analyst/indicators/last_edit/indicator.py

@@ -1,12 +1,11 @@
 import logging
 from io import StringIO
 from string import Template
-from typing import Union
 
 import matplotlib.patches as mpatches
 import matplotlib.pyplot as plt
 from dateutil.relativedelta import relativedelta
-from geojson import MultiPolygon, Polygon
+from geojson import Feature
 
 from ohsome_quality_analyst.base.indicator import BaseIndicator
 from ohsome_quality_analyst.ohsome import client as ohsome_client
@@ -16,12 +15,12 @@ class LastEdit(BaseIndicator):
     def __init__(
         self,
         layer_name: str,
-        bpolys: Union[Polygon, MultiPolygon],
+        feature: Feature,
         time_range: str = None,
     ) -> None:
         super().__init__(
             layer_name=layer_name,
-            bpolys=bpolys,
+            feature=feature,
         )
         self.time_range = time_range
         # TODO: thresholds might be better defined for each OSM layer
@@ -41,13 +40,13 @@ async def preprocess(self) -> bool:
 
         query_results_contributions = await ohsome_client.query(
             layer=self.layer,
-            bpolys=self.bpolys,
+            bpolys=self.feature.geometry,
             time=self.time_range,
             endpoint="contributions/latest/centroid",
         )
         query_results_totals = await ohsome_client.query(
             layer=self.layer,
-            bpolys=self.bpolys,
+            bpolys=self.feature.geometry,
         )
         if query_results_contributions is None or query_results_totals is None:
             return False